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arXiv:2602.19232v1 Announce Type: new Abstract: Online support communities have become vital spaces offering varied forms of support to individuals facing mental health challenges. Despite the...
arXiv:2602.19237v1 Announce Type: new Abstract: Tabular foundation models aim to make machine learning accessible for enterprise data without task-specific training. This paper presents the first...
arXiv:2602.19238v1 Announce Type: new Abstract: Spatially distributed cavity (SDC) lasers are a promising technology for simultaneous light information and power transfer (SLIPT), offering benefits such...
arXiv:2602.19240v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances the reasoning ability of Large Language Models (LLMs) by dynamically integrating external knowledge, thereby mitigating hallucinations...
arXiv:2602.19242v1 Announce Type: new Abstract: Hierarchical Navigable Small World (HNSW) has demonstrated impressive accuracy and low latency for high-dimensional nearest neighbor searches. However, its high...
arXiv:2602.19243v1 Announce Type: new Abstract: Creating webpages requires generating content and arranging layout while iteratively refining both to achieve a coherent design, a process that...
arXiv:2602.19244v1 Announce Type: new Abstract: On-the-fly Directed Controller Synthesis (OTF-DCS) mitigates state-space explosion by incrementally exploring the system and relies critically on an exploration policy...
arXiv:2602.19248v1 Announce Type: new Abstract: The collection and detection of video anomaly data has long been a challenging problem due to its rare occurrence and...
arXiv:2602.19252v1 Announce Type: new Abstract: Underwater localization is essential for marine exploration and autonomous underwater operations, yet existing radio frequency and optical approaches are limited...
arXiv:2602.19253v1 Announce Type: new Abstract: Fuzzy systems show strong potential in explainable AI due to their rule-based architecture and linguistic variables. Existing approaches navigate the...
arXiv:2602.19254v1 Announce Type: new Abstract: Precise spatial control in diffusion-based style transfer remains challenging. This challenge arises because diffusion models treat style as a global...
arXiv:2602.19260v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently been proposed as a pathway toward generalist robotic policies capable of interpreting natural language and...
arXiv:2602.19261v1 Announce Type: new Abstract: Reinforcement learning fine-tuning has proven effective for steering generative diffusion models toward desired properties in image and molecular domains. Graph...
arXiv:2602.19265v1 Announce Type: new Abstract: Solving partial differential equations (PDEs) by neural networks as well as Kolmogorov-Arnold Networks (KANs), including physics-informed neural networks (PINNs), physics-informed...
arXiv:2602.19268v1 Announce Type: new Abstract: This brief presents a runtime-adaptive, performance-enhanced vector engine featuring a low-resource, iterative CORDIC-based MAC unit for edge AI acceleration. The...
arXiv:2602.19270v1 Announce Type: new Abstract: Risk matrices (heatmaps) are widely used for information and cyber risk management and decision-making, yet they are often too coarse...
arXiv:2602.19271v1 Announce Type: new Abstract: Second-order optimizers can significantly accelerate large-scale training, yet their naive federated variants are often unstable or even diverge on non-IID...
arXiv:2602.19273v1 Announce Type: new Abstract: In this paper, we propose a novel vision-based control algorithm for regulating the whole body shape of extensible multisection soft...
arXiv:2602.19274v1 Announce Type: new Abstract: We introduce a gradient-free framework for identifying minimal, sufficient, and decision-preserving explanations in vision models by isolating the smallest subset...
arXiv:2602.19275v1 Announce Type: new Abstract: Large language models (LLMs) acquire a large amount of knowledge through pre-training on vast and diverse corpora. While this endows...
arXiv:2602.19276v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong performance on the UI-to-code task, which aims to generate UI code from...
arXiv:2602.19278v1 Announce Type: new Abstract: Industrial fruit inspection systems must operate reliably under dense multi-object interactions and continuous motion, yet most existing works evaluate detection...
arXiv:2602.19281v1 Announce Type: new Abstract: The test-time compute strategy, such as Chain-of-Thought (CoT), has significantly enhanced the ability of large language models to solve complex...
arXiv:2602.19285v1 Announce Type: new Abstract: Clinical MRI contrast acquisition suffers from inefficient information yield, which presents as a mismatch between the risky and costly acquisition...